Abstract
The major goal of radiomics studies is the identification of predictive and reliable markers. It is, therefore, crucial to account for unwanted confounding effects that affect the radiomic features like scanning noise, annotator bias, or the used imaging device and parameter. Usually, these confounding effects are not sufficiently represented in the main cohort of radiomics studies and consequently are investigated in smaller side-studies.
Chapter PDF
Similar content being viewed by others
References
Götz M, Maier-Hein KH. Optimal statistical incorporation of independent feature stability information into radiomics studies. Sci Rep. 2020 01;10(737):2045–2322.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Der/die Autor(en), exklusiv lizenziert durch Springer Fachmedien Wiesbaden GmbH, ein Teil von Springer Nature
About this paper
Cite this paper
Götz, M., Maier-Hein, K. (2021). Abstract: Data Augmentation for Information Transfer. In: Palm, C., Deserno, T.M., Handels, H., Maier, A., Maier-Hein, K., Tolxdorff, T. (eds) Bildverarbeitung für die Medizin 2021. Informatik aktuell. Springer Vieweg, Wiesbaden. https://doi.org/10.1007/978-3-658-33198-6_34
Download citation
DOI: https://doi.org/10.1007/978-3-658-33198-6_34
Published:
Publisher Name: Springer Vieweg, Wiesbaden
Print ISBN: 978-3-658-33197-9
Online ISBN: 978-3-658-33198-6
eBook Packages: Computer Science and Engineering (German Language)